Standardization of Questions in Rare Disease Registries: The PRISM Library Project
Bibliographic record
Abstract
BACKGROUND: Patient registries are often a helpful first step in estimating the impact and understanding the etiology of rare diseases - both requisites for the development of new diagnostics and therapeutics. The value and utility of patient registries rely on the use of both well-constructed structured research questions and relevant answer sets accompanying them. There are currently no clear standards or specifications for developing registry questions, and there are no banks of existing questions to support registry developers. OBJECTIVE: This paper introduces the [Rare Disease] PRISM (Patient Registry Item Specifications and Metadata for Rare Disease) project, a library of standardized questions covering a broad spectrum of rare diseases that can be used to support the development of new registries, including Internet-based registries. METHODS: A convenience sample of questions was identified from well-established (>5 years) natural history studies in various diseases and from several existing registries. Face validity of the questions was determined by review by many experts (both terminology experts at the College of American Pathologists (CAP) and research and informatics experts at the University of South Florida (USF)) for commonality, clarity, and organization. Questions were re-worded slightly, as needed, to make the full semantics of the question clear and to make the questions generalizable to multiple diseases where possible. Questions were indexed with metadata (structured and descriptive information) using a standard metadata framework to record such information as context, format, question asker and responder, and data standards information. RESULTS: At present, PRISM contains over 2,200 questions, with content of PRISM relevant to virtually all rare diseases. While the inclusion of disease-specific questions for thousands of rare disease organizations seeking to develop registries would present a challenge for traditional standards development organizations, the PRISM library could serve as a platform to liaison between rare disease communities and existing standardized controlled terminologies, item banks, and coding systems. CONCLUSIONS: If widely used, PRISM will enable the re-use of questions across registries, reduce variation in registry data collection, and facilitate a bottom-up standardization of patient registries. Although it was initially developed to fulfill an urgent need in the rare disease community for shared resources, the PRISM library of patient-directed registry questions can be a valuable resource for registries in any disease - whether common or rare. TRIAL REGISTRATION: N/A.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".